1. Technical Field
The invention relates to image processing and, more particularly, to cross talk correction within digital image processing schemes.
2. Related Art
Many conventional methods that are geared to perform cross talk correction within digital image processing schemes commonly employ a single pass method over the entire digital image that inherently does not provide a high degree of accuracy. The cross talk correction often does not converge in a highly accurate manner, given the use of only a single iteration of cross talk correction. Those conventional methods that seek to employ multi-pass cross talk correction commonly employ a frame buffer for intermediate data storage. This manner of performing cross talk correction in a multi-pass technique is radically expensive in terms of memory requirements. That is to say, the entire image needs to be stored as an intermediary to perform a multi-pass technique. For example, a single image can contain over] million bytes of memory for a SXGA image. These processing requirements commonly lead design engineers to generate cross talk correction methods that provide less than full correction. Given the enormous memory requirements, designers are often bound to solutions that do not provide full cross talk correction, at least not to convergence of whatever correction method is employed, within image data processing systems that do not have extremely large hardware budget.
In addition to those methods that inherently require enormous memory requirements, other conventional methods have sought to perform cross talk correction in a predetermined sequence. For example, in an RGB (red, green, blue) image, the red or R pixels are corrected first, the green or G pixels are corrected next, and finally the blue or B pixels are corrected. However, some of the deficiencies include significant irregularities and uneven distribution over all of the pixel colors within the image. A large amount of image processing is performed on some of the pixels within the digital image, while little to no image processing is performed on other pixels within the same digital image. These irregularities commonly result in high cost and difficulty in implementation in hardware. The amount of redesigning and debugging required to accommodate all of the various and different digital image types may be enormous. For example, to accommodate one digital image type, the designer must specifically design a method adaptable to that image type. Similarly, to accommodate another digital image type, the designer must specifically design another method adaptable to that image type. There simply lacks the ability to adapt such a conventional method universally to different types of digital images
For a clearer understanding of the problem associated with cross talk, the following illustration is provided showing the diffusion of light from one pixel into its neighbors. Cross talk between neighboring pixels in a digital image occurs when a beam of light aimed for a pixel diffuses into its neighboring pixels and corrupts their values. Using the following image pattern for illustration, when light is aimed at pixel B1, a majority of the light aimed at the pixel may in fact be captured by the pixel B1.
Line 1R1m G1m R2m G2m . . .Line 2G3m B1m G4m B2m . . .Line 3R3m G5m R4m G6m . . .Line 4G7m B3m G8m B4m . . .. . .. . .As mentioned above, there simply does not exist a highly efficient method to perform digital image processing that reduces the undesirable cross talk diffusion between neighboring pixels. The image captured inherently contains the embedded cross talk resulting from the imperfections within the image sensor itself, in that, the pixels of adjacent pixels are not perfectly isolated from one another. Further limitations and disadvantages of conventional and traditional systems will become apparent to one of skill in the art through comparison of such systems with the invention as set forth in the remainder of the present application with reference to the drawings.
Line 1R1 G1 R2 G2 . . .Line 2G3 B1 G4 B2 . . .Line 3R3 G5 R4 G6 . . .Line 4G7 B3 G8 B4 . . .. . .. . .However, some of the light escapes into the neighboring pixels R1, G1, R2, G3, G4, R3, G5, and R4. This undesirable diffusion is color dependent and can be modeled by the following equations for each pixel color:B1m=b1*B1+b2*G1+b3*G5+b4*G3+b5*G4+b6*R1+b7*R2+b8*R3+b9*R4R4m=r1*R4+r2*G4+r3*G5+r4*G6+r5*G8+r6*B1+r7*B2+r8*B3+r9*B4G4m=g1*G4+g2*G1+g3*G2+g4*G5+g5*G6+g6*B1+g7*B2+g8*R2+g9*R4where the left hand side of the preceding equations are the cross talk corrupted pixel values and the coefficients preceding the pixel values on the right hand side (b1 . . . b9, r1 . . . r9, and g1 . . . g9) represent the diffusion coefficients between the adjacent pixels. The actual values captured by the digital image sensor are corrupted and are represented as follows:
Line 1 R1m G1m R2m G2m . . .